Natural Capital Evolution and Driving Forces in Energy-Rich and Ecologically Fragile Regions: A Case Study of Ningxia Province, China

Abstract

Ningxia Province is rich in energy but fragile in ecology. How to coordinate sustainable utilization of natural capital and the fragile ecological environment is a significant guarantee for social-economic development. This study uses the improved three-dimensional ecological footprint to characterize the utilization status of natural capital flows and stocks in Ningxia Province from 2004 to 2017. Additionally, the driving factors behind changes in the natural capital stock are revealed by the partial least squares method (PLS). The results are as follows: (1) From 2004 to 2017, ecological footprint increased rapidly in Ningxia Province at an annual rate of 4.52%, resulting in a increase of the ecological deficit from 1.64 to 3.85 gha/cap at an annual rate of 6.8%, among which, Yinchuan city and Shizuishan city had the largest ecological deficit, while Guyuan city basically maintained ecological surplus. The fossil energy land and cropland were the main components of ecological footprint. (2) The consumption of capital stock in Ningxia Province continued to grow at an annual rate of 3.12%, from a value of 2.28 times overusing the existing area in 2004, increasing to 3.41 times in 2017. While the EF size increased slightly with an annual rate of 1.95%. The capital stock consumption was concentrated in Yinchuan and Shizuishan, and the capital flow consumption was concentrated in Wuzhong, Guyuan, and Zhongwei. (3) The capital flows of forest land and built-up land basically meet consumption demand, while the capital stock occupation of grassland, water and fossil energy land was serious. By 2017, the capital flow of cropland could basically satisfy people’s consumption demand. (4) The urbanization rate, GDP, the secondary industry output value and per capita consumption expenditure of urban residents were the main influence factors on the natural capital stock consumption. These findings not only are of real significance in promoting the coordinated development between economy and natural capital utilization in Ningxia Province but also have policy implications in improving the utilization efficiency of natural capital in energy-rich ecologically fragile regions.

Decoupling and Decomposition Analysis of Land Natural Capital Utilization and Economic Growth: A Case Study in Ningxia Hui Autonomous Region, China

“…It is noted that if the energy footprint was incorporated into the forestland to calculate the footprint depth according to the practice of Niccolucci [ 19 ], the forestland footprint depth of Ningxia in 2017 was up to 12.69 [ 60 ], which is obviously too pessimistic to reflect the actual situation of the local forest ecosystem.…”

Does the Price Support Policy Drive a Balanced Distribution of Profits in the Chinese Dairy Supply Chain? Implications for Supplier and Consumer Psychology

“…In fact, the parallel trend test was just a necessary precondition for the application of DID. The conformance of the study object to the postulated condition did not mean that the results of the coefficient of the interaction variable reflected the policy effect more than other effects (Guo et al, 2020;Liu et al, 2020;Mao et al, 2020). One important consideration regards the influence of uncontrolled regional time-varying characteristics and undetected factors on estimation results.…”

Landscape Impacts on Ecosystem Service Values Using the Image Fusion Approach

“…An arid to semiarid climatic pattern is visualized in the majority of counties except for the Yellow River basin which flows 397 km around 12 counties in the province [27]. Civilization is principally around the Yellow River and its tributaries and nearly half the GDP of the province is based on the production of grains and agricultural output value carried out in this basin while the rest of the area is of grasslands due to its semiarid climate [28]. The province has 22 county-level divisions for administrative purposes with 5 prefectural cities and the population is estimated to be around 7 million [29].…”